The examination of heart sounds provides a good and well proven way to assess the physical condition of the heart of a patient during a physical examination. In its classical form, the examination of heart sounds only requires a stethoscope and a physician who is experienced in interpreting the sounds he or she hears. By placing the stethoscope at different positions on the chest of the patient, it is possible to filter out different components of the heart sound. Thus, the heart sound may be separated into its components because the complete heart sound is produced by several sound sources distributed in and around the heart. The heart valves produce the most perceptible sounds. Another source of heart sounds is turbulent flow of blood which produces so called heart murmurs.
The frequency of primary heart sounds lies in the low frequency region where the sensitivity of the human ear is low. The occurrence of closely spaced cardiac events within the short cycle duration of a non-stationary heart sound signal makes it difficult to analyze the heart sounds. Computer-aided digital signal processing methods have been used to overcome these limitations.
A number of methodologies have been reported for the acquisition and analysis of heart sounds and of phonocardiogram signals which may be understood as a representation of the heart sounds in some other format, for example recorded on paper, magnetic tape, or in a digital format stored by a data processing system. Many other kinds of representing a heart sound as a phonocardiogram signal (PCG) are also possible and shall be encompassed by the term phonocardiogram.
Some techniques for automatically evaluating a phonocardiogram signal follow a black box approach wherein the input is the PCG signal along with an auxiliary electrocardiogram (ECG) signal. The output is based purely on the statistical processing of the PCG signal and optionally the ECG signal. An example for automatic analysis of heart sounds is presented in the article “Heart sound segmentation algorithm based on instantaneous energy of electrocardiogram” by Malarvini et al., published in 2003 in “Computers in Cardiology”, pages 327-330. In 1987, Lehner and Rangayyan wrote their article “A three channel microcomputer system for segmentation and characterization of the phonocardiogram”, published in “IEEE Transactions on Biomedical Engineering”, 34. As early as 1962, Gerbarg et al. published their article “Analysis of phonocardiogram by a digital computer” in “Circulation Research”, 11, pages 569-576. When, in known techniques, an auxiliary ECG signal is used, the ECG signal usually only assists in segmenting the PCG signal.
In some cases the need of an auxiliary signal is eliminated or a different auxiliary signal is used but the analysis is still purely based on the content of the PCG signal.
Examples can be found in the following articles:
Liang H. et al. (1997): “A heart sound segmentation algorithm using wavelet decomposition and reconstruction”, Engineering in Medicine and Biology society, 4, pp. 1630-1633.
Gamero L. G. and Watrous R. (2003): “Detection of the first and second heart sound using probabilistic models”, Engineering in Medicine and Biology society, 25th Intl. Conf., pp. 2877-2880.
Omran S. and Tayel M. (2004): “A heart sound segmentation and feature extraction algorithm using wavelets”, First Intl. symposium on control, communication and signal processing, pp. 235-238.
Sharif Z. et al. (2000): “Analysis and classification of heart sounds and murmurs based on the instantaneous energy and frequency estimations”, TENCON 2000 Proceedings, 2, pp. 130-134.
The focus of the existing techniques is either to provide a better representation of the cardiac events of the PCG signal or to present an automatic classifier system to predict cardiac disorders. The quality of diagnosis of a cardiac disorder may be improved by combining the analysis of the PCG signal with additional information, such as biomedical parameters of the patient (age group, gender, average heart rate, medical history, physical signatures, etc.). U.S. Pat. No. 5,687,738 (Shapiro et al.) and U.S. Pat. No. 6,572,560 B1 (Watrous et al.) describe techniques for analyzing heart sounds that take into account the medical history of the patient.
United States Patent Application No. US2005/0090755A 1 (Guion et al.) describes an analysis of auscultatory sounds using single value decomposition. The analysis iterates through known physiological conditions and their associated heart sounds. During each iteration a similarity measure between the captioned heart sounds and those heart sounds associated with the given physiological condition is determined. The analysis produces a result based on the most similar heart sound.